Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes

Guy Rosman; Michael M. Bronstein; Alexander M. Bronstein; Alon Wolf; Ron Kimmel

doi:10.1007/978-3-642-24785-9_61

Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes

Guy Rosman, Michael M. Bronstein, Alexander M. Bronstein, Alon Wolf, Ron Kimmel^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Understanding of articulated shape motion plays an important role in many applications in the mechanical engineering, movie industry, graphics, and vision communities. In this paper, we study motion-based segmentation of articulated 3D shapes into rigid parts. We pose the problem as finding a group-valued map between the shapes describing the motion, forcing it to favor piecewise rigid motions. Our computation follows the spirit of the Ambrosio-Tortorelli scheme for Mumford-Shah segmentation, with a diffusion component suited for the group nature of the motion model. Experimental results demonstrate the effectiveness of the proposed method in non-rigid motion segmentation.

Original language	English
Title of host publication	Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers
Pages	725-736
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-642-24785-9_61
State	Published - 2012
Externally published	Yes
Event	3rd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2011 - Ein-Gedi, Israel Duration: 29 May 2011 → 2 Jun 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6667 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2011
Country/Territory	Israel
City	Ein-Gedi
Period	29/05/11 → 2/06/11

Keywords

Ambrosio-Tortorelli
Lie-groups
Motion Segmentation
Surface Diffusion

Access to Document

10.1007/978-3-642-24785-9_61

Cite this

Rosman, G., Bronstein, M. M., Bronstein, A. M., Wolf, A., & Kimmel, R. (2012). Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes. In Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers (pp. 725-736). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6667 LNCS). https://doi.org/10.1007/978-3-642-24785-9_61

Rosman, Guy ; Bronstein, Michael M. ; Bronstein, Alexander M. et al. / Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes. Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers. 2012. pp. 725-736 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Understanding of articulated shape motion plays an important role in many applications in the mechanical engineering, movie industry, graphics, and vision communities. In this paper, we study motion-based segmentation of articulated 3D shapes into rigid parts. We pose the problem as finding a group-valued map between the shapes describing the motion, forcing it to favor piecewise rigid motions. Our computation follows the spirit of the Ambrosio-Tortorelli scheme for Mumford-Shah segmentation, with a diffusion component suited for the group nature of the motion model. Experimental results demonstrate the effectiveness of the proposed method in non-rigid motion segmentation.",

keywords = "Ambrosio-Tortorelli, Lie-groups, Motion Segmentation, Surface Diffusion",

author = "Guy Rosman and Bronstein, {Michael M.} and Bronstein, {Alexander M.} and Alon Wolf and Ron Kimmel",

year = "2012",

doi = "10.1007/978-3-642-24785-9_61",

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Rosman, G, Bronstein, MM, Bronstein, AM, Wolf, A & Kimmel, R 2012, Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes. in Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6667 LNCS, pp. 725-736, 3rd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2011, Ein-Gedi, Israel, 29/05/11. https://doi.org/10.1007/978-3-642-24785-9_61

Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes. / Rosman, Guy; Bronstein, Michael M.; Bronstein, Alexander M. et al.
Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers. 2012. p. 725-736 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6667 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Rosman G, Bronstein MM, Bronstein AM, Wolf A, Kimmel R. Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes. In Scale Space and Variational Methods in Computer Vision - Third International Conference, SSVM 2011, Revised Selected Papers. 2012. p. 725-736. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-24785-9_61

Group-valued regularization framework for motion segmentation of dynamic non-rigid shapes

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